Niobium nitride (NbN) is a useful material for fabricating detectors because of its high critical temperature and relatively high kinetic inductance. In particular, NbN can be used to fabricate nanowire detectors and mm-wave transmission lines. When deposited, NbN is usually sputtered, leaving room for concern about uniformity at small thicknesses. We present Atomic Layer Deposition niobium nitride (ALD NbN) as an alternative technique that allows for precision control of deposition parameters such as film thickness, stage temperature, and nitrogen flow. Atomic-scale control over film thickness admits wafer-scale uniformity for films 4-30 nm thick; control over deposition temperature gives rise to growth rate changes, which can be used to optimize film thickness and critical temperature. In order to characterize ALD NbN in the radio-frequency regime, we construct single-layer microwave resonators and test their performance as a function of stage temperature and input power. ALD processes can admit high resonator quality factors, which in turn increase detector multiplexing capabilities. We present measurements of the critical temperature and internal quality factor of ALD NbN resonators under the variation of ALD parameters.
We report on the extended infrared single-photon response of niobium nitride superconducting nanowires deposited by atomic layer deposition. The superconducting nanowire single-photon detectors are based on 4.65 nm thick NbN, patterned into 100 nm meanders, and characterized at 2.5 K. We verify single-photon sensitivity from 1310 to 2006 nm with saturated response at shorter wavelengths.
High-resolution late gadolinium enhancement imaging is a powerful tool for arrhythmia risk assessment post-myocardial infarction, but requires substantial operator time and expertise to analyze. To address this challenge, automated analysis is introduced to isolate and depict relevant image features corresponding to healthy myocardium, peri-infarct gray zone, and dense scar. Using two sets of manual epicardial and endocardial contours, weighted total variation denoising is used to correct for statistical noise, and persistent homology is used to stratify topological features of the image. K-means clustering was used to generate remote myocardium and dense scar signal intensities for automated FWHM thresholding.
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